predict_fof_pc: Use a function-on-function linear regression model for...

Description Usage Arguments Value References

View source: R/02_fof_pc.R

Description

Predict new observations of the functional response variable and calculate the corresponding prediction error (and their standardized or studentized version) given new observations of functional covariates and a fitted function-on-function linear regression model.

Usage

1
predict_fof_pc(object, mfdobj_y_new, mfdobj_x_new)

Arguments

object

A list obtained as output from fof_pc, i.e. a fitted function-on-function linear regression model.

mfdobj_y_new

An object of class mfd containing new observations of the functional response.

mfdobj_x_new

An object of class mfd containing new observations of the functional covariates.

Value

A list of mfd objects. It contains:

* pred_error: the prediction error of the standardized functional response variable,

* pred_error_original_scale: the prediction error of the functional response variable on the original scale,

* y_hat_new: the prediction of the functional response observations on the original scale,

* y_z_new: the standardized version of the functional response observations provided in mfdobj_y_new,

* y_hat_z_new: the prediction of the functional response observations on the standardized/studentized scale.

References

Centofanti F, Lepore A, Menafoglio A, Palumbo B, Vantini S. (2020) Functional Regression Control Chart. Technometrics. <doi:10.1080/00401706.2020.1753581>


funcharts documentation built on March 15, 2021, 5:07 p.m.